Entities that are engaged in commerce are often interested in finding out as much information about their customers as they can. Such information can be useful in earning repeat business, finding and enticing new customers, and ensuring higher customer satisfaction, all of which may lead to increased revenue and returns. For the customers, merchants and other entities that learn more about them may lead to the availability of more attractive deals, offers, and other benefits to the customer, encouraging the customer to share their information with the entities. As a result, it can be beneficial to both entities and their customers for an entity to learn more about its customers.
However, many customers may transact with a vast number of entities. In such cases, there may be a significant number of entities that desire to learn more about a customer, which the customer may be uncomfortable with. In addition, a customer may transact with several entities very rarely, or even just once, with little to no intention of returning to the entity for future transactions, such as due to location, bad customer service, etc. In such cases, there may be little advantage to the entity learning more about the consumer. Thus, traditional methods for distributing insights about customers to associated entities often result in a distribution of data that is far too wide for customer comfort, and result in data being distributed to entities that may find little to no use for such data. However, presenting insights about select consumers to those most likely to benefit from them presents technological challenges, particularly on a large scale on tens or hundreds of thousands of consumers, particularly in an automated fashion.
Accordingly, there is a need for a technological solution for providing insights on customers of entities to only entities that desire such information and based on the propensity for the customer to continually interact with the entity, to provide greater consumer benefit and a higher rate of return on the usage of such information.